Association Rule-Based Feature Mining for Automated Fault Diagnosis of Rolling Bearing
Effective and efficient diagnosis methods are highly demanded to improve system reliability. Comparing with conventional fault diagnosis methods taking a forward approach (e.g., feature extraction, feature selection, and fusion, and then fault diagnosis), this paper presents a new association rule m...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/1518246 |
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